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      "name": "2.2.4 Temporal Invariance",
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        "<a href=\"https://colab.research.google.com/github/Farmhouse121/Adventures-in-Financial-Data-Science/blob/main/Book/Section%202.2%20Abnormality%20of%20Financial%20Distributions/Section%202.2.4%20Temporal%20Invariance.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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          "text": [
            "Installing yfinance and getting the data...\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
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              "                   Open         High          Low        Close    Adj Close  \\\n",
              "Date                                                                          \n",
              "1957-03-04    44.060001    44.060001    44.060001    44.060001    44.060001   \n",
              "1957-03-05    44.220001    44.220001    44.220001    44.220001    44.220001   \n",
              "1957-03-06    44.230000    44.230000    44.230000    44.230000    44.230000   \n",
              "1957-03-07    44.209999    44.209999    44.209999    44.209999    44.209999   \n",
              "1957-03-08    44.070000    44.070000    44.070000    44.070000    44.070000   \n",
              "...                 ...          ...          ...          ...          ...   \n",
              "2022-03-17  4345.109863  4412.669922  4335.649902  4411.669922  4411.669922   \n",
              "2022-03-18  4407.339844  4465.399902  4390.569824  4463.120117  4463.120117   \n",
              "2022-03-21  4462.399902  4481.750000  4424.299805  4461.180176  4461.180176   \n",
              "2022-03-22  4469.100098  4522.000000  4469.100098  4511.609863  4511.609863   \n",
              "2022-03-23  4493.100098  4496.240234  4473.490234  4483.830078  4483.830078   \n",
              "\n",
              "                  Volume    Return  \n",
              "Date                                \n",
              "1957-03-04  1.890000e+06  0.731595  \n",
              "1957-03-05  1.860000e+06  0.363141  \n",
              "1957-03-06  1.840000e+06  0.022610  \n",
              "1957-03-07  1.830000e+06 -0.045219  \n",
              "1957-03-08  1.630000e+06 -0.316669  \n",
              "...                  ...       ...  \n",
              "2022-03-17  4.174170e+09  1.234782  \n",
              "2022-03-18  6.681510e+09  1.166229  \n",
              "2022-03-21  3.961050e+09 -0.043466  \n",
              "2022-03-22  3.962880e+09  1.130411  \n",
              "2022-03-23  4.998118e+08 -0.615740  \n",
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              "      <th>Open</th>\n",
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              "      <th>1957-03-04</th>\n",
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              "      <th>1957-03-05</th>\n",
              "      <td>44.220001</td>\n",
              "      <td>44.220001</td>\n",
              "      <td>44.220001</td>\n",
              "      <td>44.220001</td>\n",
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              "      <th>1957-03-06</th>\n",
              "      <td>44.230000</td>\n",
              "      <td>44.230000</td>\n",
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              "      <th>1957-03-07</th>\n",
              "      <td>44.209999</td>\n",
              "      <td>44.209999</td>\n",
              "      <td>44.209999</td>\n",
              "      <td>44.209999</td>\n",
              "      <td>44.209999</td>\n",
              "      <td>1.830000e+06</td>\n",
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              "      <th>1957-03-08</th>\n",
              "      <td>44.070000</td>\n",
              "      <td>44.070000</td>\n",
              "      <td>44.070000</td>\n",
              "      <td>44.070000</td>\n",
              "      <td>44.070000</td>\n",
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          "metadata": {},
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      ],
      "source": [
        "print(\"Installing yfinance and getting the data...\")\n",
        "!pip install yfinance 1>/dev/null\n",
        "from yfinance import download\n",
        "import pandas as pd\n",
        "import numpy as np ;\n",
        "import matplotlib.pyplot as pl\n",
        "from statsmodels.base.model import GenericLikelihoodModel\n",
        "from datetime import datetime\n",
        "zero,one,two,five,hundred=0e0,1e0,2e0,5e0,1e2 # some friendly numbers\n",
        "half,GoldenRatio=one/two,(one+np.sqrt(five))/two\n",
        "\n",
        "# get the daily returns of the S&P 500 \n",
        "SPX=download('^GSPC','1957-03-01').dropna()\n",
        "SPX['Return']=SPX['Adj Close'].pct_change()*hundred\n",
        "SPX.index=pd.DatetimeIndex(SPX.index).to_period('D')\n",
        "SPX.dropna(inplace=True)\n",
        "SPX.loc[SPX[\"Volume\"]==0,\"Volume\"]=np.nan\n",
        "SPX"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# year on year F statistics for variance of returns\n",
        "from scipy.stats import f\n",
        "variance=pd.DataFrame({\"v1\":SPX[\"Return\"].groupby(SPX.index.year).var(),\"n1\":SPX[\"Return\"].groupby(SPX.index.year).count()})\n",
        "variance[\"v2\"]=variance[\"v1\"].shift()\n",
        "variance[\"n2\"]=variance[\"n1\"].shift()\n",
        "variance[\"F\"]=variance[\"v1\"]/variance[\"v2\"]\n",
        "variance[\"p\"]=list(map(lambda i:one-f.cdf(variance.loc[i,\"F\"],variance.loc[i,\"n1\"],variance.loc[i,\"n2\"]),variance.index))\n",
        "variance.dropna(inplace=True)\n",
        "nt,alpha=variance.shape[0],0.05\n",
        "nf=variance[variance[\"p\"]<=alpha].shape[0]\n",
        "display(variance)\n",
        "\n",
        "# Figure 2.5\n",
        "figure,plot=pl.subplots(figsize=(10*GoldenRatio,10))\n",
        "variance['F'].plot(ax=plot,color='blue')\n",
        "figure.suptitle('\\nF-Test for Constant Variance of S&P 500 Index',fontsize=22)\n",
        "plot.set_title('%d Years of Daily Data from %s to %s, %d/%d F-Test Failures at Critical Value %.2f' % (variance.shape[0],SPX.index[0],SPX.index[-1],nf,nt,alpha),fontsize=18)\n",
        "plot.set_ylabel(\"F Statistic\",fontsize=14)\n",
        "\n",
        "for year in variance.index[variance[\"p\"]<=alpha]:\n",
        "    plot.axvspan(year-0.5,year+0.5,alpha=0.1)\n",
        "\n",
        "plot.set_xlabel(None)\n",
        "plot.set_ylim(0,None);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "wNqwBZ61d0v7",
        "outputId": "3bb827f4-cb88-4626-9b8c-9c3f8a00302c"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "            v1   n1        v2     n2         F             p\n",
              "Date                                                        \n",
              "1958  0.320143  252  0.707628  210.0  0.452418  1.000000e+00\n",
              "1959  0.350320  253  0.320143  252.0  1.094259  2.373847e-01\n",
              "1960  0.428305  252  0.350320  253.0  1.222611  5.545160e-02\n",
              "1961  0.406079  250  0.428305  252.0  0.948107  6.633016e-01\n",
              "1962  1.085471  252  0.406079  250.0  2.673056  1.199041e-14\n",
              "...        ...  ...       ...    ...       ...           ...\n",
              "2018  1.153792  251  0.177373  251.0  6.504876  1.110223e-16\n",
              "2019  0.617271  252  1.153792  251.0  0.534993  9.999996e-01\n",
              "2020  4.704339  253  0.617271  252.0  7.621188  1.110223e-16\n",
              "2021  0.681002  252  4.704339  253.0  0.144760  1.000000e+00\n",
              "2022  1.875898   56  0.681002  252.0  2.754615  3.827581e-08\n",
              "\n",
              "[65 rows x 6 columns]"
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              "      <th>1958</th>\n",
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              "      <td>5.545160e-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1961</th>\n",
              "      <td>0.406079</td>\n",
              "      <td>250</td>\n",
              "      <td>0.428305</td>\n",
              "      <td>252.0</td>\n",
              "      <td>0.948107</td>\n",
              "      <td>6.633016e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1962</th>\n",
              "      <td>1.085471</td>\n",
              "      <td>252</td>\n",
              "      <td>0.406079</td>\n",
              "      <td>250.0</td>\n",
              "      <td>2.673056</td>\n",
              "      <td>1.199041e-14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>1.153792</td>\n",
              "      <td>251</td>\n",
              "      <td>0.177373</td>\n",
              "      <td>251.0</td>\n",
              "      <td>6.504876</td>\n",
              "      <td>1.110223e-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>0.617271</td>\n",
              "      <td>252</td>\n",
              "      <td>1.153792</td>\n",
              "      <td>251.0</td>\n",
              "      <td>0.534993</td>\n",
              "      <td>9.999996e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>4.704339</td>\n",
              "      <td>253</td>\n",
              "      <td>0.617271</td>\n",
              "      <td>252.0</td>\n",
              "      <td>7.621188</td>\n",
              "      <td>1.110223e-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021</th>\n",
              "      <td>0.681002</td>\n",
              "      <td>252</td>\n",
              "      <td>4.704339</td>\n",
              "      <td>253.0</td>\n",
              "      <td>0.144760</td>\n",
              "      <td>1.000000e+00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022</th>\n",
              "      <td>1.875898</td>\n",
              "      <td>56</td>\n",
              "      <td>0.681002</td>\n",
              "      <td>252.0</td>\n",
              "      <td>2.754615</td>\n",
              "      <td>3.827581e-08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>65 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9e7fe7ee-9158-400a-bc20-344e6585f205')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9e7fe7ee-9158-400a-bc20-344e6585f205 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9e7fe7ee-9158-400a-bc20-344e6585f205');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1164.98x720 with 1 Axes>"
            ],
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "GrJXrm4_8YPT"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}
